Detection of Twitter Bots and Cyber Bullying Using Machine Learning

An adding number of people on twitter but hide their identity for nasty purpose. It's dangerous for other druggies hence the necessity for relating the twitter bots. therefore there's a developing need for distinguishing which regard contains bots or not. The characteristics of twitter accounts are employed as Features in machine literacy algorithms to marker druggies as genuine or fake. In this paper, we used three machine literacy algorithms to descry the account is fake or real, which are Decision Tree, Random Forest, and Multinomial Naive Bayes The delicacy given by the Decision tree algorithm is 93, the Random Forest algorithm is 90 and the Multinomial Naive Bayes is 89. numerous incidents have lately passed worldwide due to online importunity, similar as participating private exchanges, rumours, and sexual reflections. thus, the identification of bullying textbook or communication on social media has gained a growing quantum of attention among experimenters. The purpose of this exploration is to design and develop an effective fashion to descry online vituperative and bullying dispatches by incorporating natural language processing and machine literacy.